Simulation‐based Finite Sample Linearity Test against Smooth Transition Models*
Andres Gonzalez and
Timo Teräsvirta
Oxford Bulletin of Economics and Statistics, 2006, vol. 68, issue s1, 797-812
Abstract:
In this paper, we use Monte Carlo (MC) testing techniques for testing linearity against smooth transition models. The MC approach allows us to introduce a new test that differs in two respects from the tests existing in the literature. First, the test is exact in the sense that the probability of rejecting the null when it is true is always less than or equal to the nominal size of the test. Secondly, the test is not based on an auxiliary regression obtained by replacing the model under the alternative by approximations based on a Taylor expansion. We also apply MC testing methods for size correcting the test proposed by Luukkonen, Saikkonen and Teräsvirta (Biometrika, Vol. 75, 1988, p. 491). The results show that the power loss implied by the auxiliary regression‐based test is non‐existent compared with a supremum‐based test but is more substantial when compared with the three other tests under consideration.
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
https://doi.org/10.1111/j.1468-0084.2006.00457.x
Related works:
Working Paper: Simulation-based finite-sample linearity test against smooth transition models (2005)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:obuest:v:68:y:2006:i:s1:p:797-812
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0305-9049
Access Statistics for this article
Oxford Bulletin of Economics and Statistics is currently edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple
More articles in Oxford Bulletin of Economics and Statistics from Department of Economics, University of Oxford Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().